This story is part of our July/August 2015 issue

The way Hod Lipson describes his Creative Machines Lab captures his ambitions: “We are interested in robots that create and are creative.” Lipson, an engineering professor at Cornell University (this July he’s moving his lab to Columbia University), is one of the world’s leading experts on artificial intelligence and robotics. His research projects provide a peek into the intriguing possibilities of machines and automation, from robots that “evolve” to ones that assemble themselves out of basic building blocks. (His Cornell colleagues are building robots that can serve as baristas and kitchen help.) A few years ago, Lipson demonstrated an algorithm that explained experimental data by formulating new scientific laws, which were consistent with ones known to be true. He had automated scientific discovery.

Lipson’s vision of the future is one in which machines and software possess abilities that were unthinkable until recently. But he has begun worrying about something else that would have been unimaginable to him a few years ago. Could the rapid advances in automation and digital technology provoke social upheaval by eliminating the livelihoods of many people, even as they produce great wealth for others?

“More and more computer-guided automation is creeping into everything from manufacturing to decision making,” says Lipson. In the last two years alone, he says, the development of so-called deep learning has triggered a revolution in artificial intelligence, and 3-D printing has begun to change industrial production processes. “For a long time the common understanding was that technology was destroying jobs but also creating new and better ones,” says Lipson. “Now the evidence is that technology is destroying jobs and indeed creating new and better ones but also fewer ones. It is something we as technologists need to start thinking about.”

Automation Angst

Technology and the Threat of a Jobless Futureby Martin Ford
Basic Books, 2015

The Great Divide:
Unequal Societies and What We Can Do About Themby Joseph E. Stiglitz
W. W. Norton, 2015

Inequality: What Can Be Done?by Anthony B. Atkinson
Harvard University Press, 2015

The Second Machine Age:
Work, Progress, and Prosperity in a Time of Brilliant Technologiesby Erik Brynjolfsson and Andrew McAfee
W. W. Norton, 2014

Worries that rapidly advancing technologies will destroy jobs date back at least to the early 19th century, during the Industrial Revolution in England. In 1821, a few years after the Luddite protests, the British economist David Ricardo fretted about the “substitution of machinery for human labour.” And in 1930, during the height of the worldwide depression, John Maynard Keynes famously warned about “technological unemployment” caused by “our discovery of means of economising the use of labour.” (Keynes, however, quickly added that “this is only a temporary phase of maladjustment.”)

Now, technology is once again under suspicion as rising income inequality confronts the United States, Europe, and much of the rest of the developed world. A recent report from the Organization for Economic Cooperation and Development concluded that the gap between the rich and poor is at a historically high level in many of its 34 member countries, driven largely by a drop in earning power for the bottom 40 percent of the population. Many of the lowest earners have seen wages decrease over the last few decades, and the OECD warns that income inequality is now undermining economic growth. Meanwhile, the erosion of the American middle class and the pressure on the lowest-paid U.S. workers has been painfully evident for years.

Only 68 percent of men between 30 and 45 who have a high school diploma were working full time in 2013, according to a recent report by the Hamilton Project at the Brookings Institution, a Washington-based public-policy group. Earnings for the typical worker haven’t kept up with the growth of the economy for decades. Median earnings for a man without a high school diploma fell 20 percent from 1990 to 2013, while wages for those with only a high school diploma dropped 13 percent. Women have fared somewhat better, though they still generally earn less than men. Over the same period, earnings for women without a high school diploma dropped 12 percent, while earnings for those with a high school diploma actually rose by 3 percent.

Do today’s rapid advances in artificial intelligence and automation portend a future in which robots and software greatly reduce the need for human workers?

It is notoriously hard to determine the factors that go into job creation and earnings, and it is particularly difficult to isolate the specific impact of technology from that of, say, globalization, economic growth, access to education, and tax policies. But advances in technology offer one plausible, albeit partial, explanation for the decline of the middle class. A prevailing view among economists is that many people simply don’t have the training and education required for the increasing number of well-paying jobs requiring sophisticated technology skills. At the same time, software and digital technologies have displaced many types of jobs involving routine tasks such as those in accounting, payroll, and clerical work, forcing many of those workers to take more poorly paid positions or simply abandon the workforce. Add to that the increasing automation of manufacturing, which has eliminated many middle-class jobs over the past decades, and you begin to see why much of the workforce is feeling squeezed.

These are long-term trends that began decades ago, says David Autor, an MIT economist who has studied “job polarization”—the disappearance of middle-skill jobs even as demand increases for low-paying manual work on the one hand and highly skilled work on the other. This “hollowing out” of ­the middle of the workforce, he says, “has been going on for a while.”

Nevertheless, the recession of 2007–2009 may have sped up the destruction of many relatively well-paid jobs requiring repetitive tasks that can be automated. These so-called routine jobs “fell off a cliff in the recession,” says Henry Siu, an economist at the University of British Columbia, “and there’s been no large rebound.” This type of work, which includes white-collar jobs in sales and administration as well as blue-collar jobs in assembly work and machine operation, makes up about 50 percent of employment in the United States. Siu’s research also shows that the disappearance of these jobs has most harshly affected people in their 20s, many of whom seem to have simply stopped looking for work.

That’s bad enough. But there’s an even more fundamental fear. Is this a harbinger of what’s to come for other sectors of the workforce, as technology takes over more and more of the jobs that have long been considered secure paths to a middle-class life? Are we at the beginning of an economic transformation that is unique in history, wonderful for what it could do in bringing us better medicine, services, and products, but devastating for those not in a position to reap the financial benefits? Will robots and software replace most human workers?

Scaring children

No one knows the answer. Many economists see little convincing evidence that advances in technology will be responsible for a net decrease in the number of jobs, or that what we’re undergoing is any different from earlier transitions when technology destroyed some jobs but improved employment opportunities over time. Still, over the last several years, a number of books and articles have argued that the recent advances in artificial intelligence and automation are inherently different from past technological breakthroughs in what they portend for the future of employment. Martin Ford is one of those who think this time is different. In his new book, Rise of the Robots: Technology and the Threat of a Jobless Future, Ford points to numerous examples of new technologies, such as driverless cars and 3-D printing, that he thinks will indeed eventually replace most workers. How then will we adapt to this “jobless future”?

Ford recommends a guaranteed basic income as part of the answer. Simply put, his prescription is to give people a modest amount of money. It’s not a new idea. One version of it, called a negative income tax, was popularized by the conservative economist Milton Friedman during the early 1960s as a way to replace some of the growing government bureaucracy. And Ford quotes ­the economist Friedrich Hayek, who in 1979 described assuring a minimum income as a way to provide “a sort of floor below which nobody need fall even when he is unable to provide for himself.” Both Richard Nixon and his 1972 presidential rival George McGovern, a liberal Democrat, championed some form of the policy.

The idea went out of fashion in the 1980s, but it has returned in recent years as a way to help those people shut out of the labor markets. In the libertarian version, it’s a way to provide a safety net with minimum government involvement; in the progressive version, it supplements other programs to help the poor.

Whether it is good politics or good social policy has been endlessly debated. Recently, others have suggested a related policy: expanding the Earned Income Tax Credit, which would give some extra money to low-paid workers. These ideas probably do make sense as a way to strengthen the social safety net. But if you believe that the rapid advance of technology could eliminate the need for most workers, such policies do little to directly address that scenario. Allowing a large number of workers to become irrelevant in the technology-centric economy would be a huge waste of human talent and ambition—and would probably put an enormous financial burden on society. What’s more, a guaranteed basic income does not offer much to those in the middle class whose jobs are at risk, or to those who have recently fallen from financial security in the absence of well-paying jobs.

It might also be premature to plan for a dystopian future of hardly any jobs. Ford’s Rise of the Robots offers many examples of impressive achievements in automation, software, and AI that could make some jobs obsolete—even those requiring highly trained professionals in fields like radiology and law. But how do you assess just how specific technologies like these will affect the total number of jobs in the economy?

In fact, there is not much evidence on how even today’s automation is affecting employment. Guy Michaels and his colleague Georg Graetz at the London School of Economics recently looked at the impact of industrial robots on manufacturing in 17 developed countries. The findings tell a mixed story: the robots did seem to replace some low-skill jobs, but their most important impact was to significantly increase the productivity of the factories, creating new jobs for other workers. Overall, there was no evidence that the robots reduced total employment, says Michaels.

If it’s difficult to quantify the effect of today’s technology on job creation, it’s impossible to accurately predict the effects of future advances. That opens the door to wild speculation. Take an extreme example raised by Ford: molecular manufacturing. As proposed by some nanotechnology boosters, most notably the author K. Eric Drexler, the idea is that one day it will be possible to build almost anything with nanoscale robots that move atoms around like tiny building blocks. Though Ford acknowledges that it might not happen, he warns that jobs will be devastated if it does.

The credence Ford gives to Drexler’s vision of nanobots slaving away in molecular factories seems less than warranted, though, given that the idea was debunked by the Nobel-­winning chemist Richard Smalley more than a decade ago (see “Will the Real Nanotech Please Stand Up?”). Smalley saw great potential for nanotech in areas such as clean energy, but his objection to molecular manufacturing as ­Drexler described it was simple: it ignores the rules of chemistry and physics governing the way atoms bind and react with each other. Smalley admonished Drexler: “You and people around you have scared our children. I don’t expect you to stop, but … while our future in the real world will be challenging and there are real risks, there will be no such monster as the self-replicating mechanical nanobot of your dreams.”

Though Ford does note Smalley’s criticism, one begins to wonder whether his conjuring the “rise of the robots” might not indeed be needlessly scaring our children. Speculating about such far-fetched possibilities is a distraction in thinking about how to address future concerns, much less existing job woes.

A more realistic, but in its way more interesting, version of the future is being written in the downtown Chicago offices of Narrative Science. Its software, called Quill, is able to take data—say, the box score of a baseball game or a company’s annual report—and not only summarize the content but extract a “narrative” from it. Already, Forbes is using it to create some stories about corporate earnings, and the Associated Press is using a rival’s product to write some sports stories. The quality is readable and is likely to improve greatly in coming years.

“Short-term and medium-term, [AI] will displace work but not necessarily jobs.”

Yet despite the potential of such technology, it is not clear how it would affect employment. “As AI stands today, we’ve not seen a massive impact on white-collar jobs,” says Kristian Hammond, a Northwestern University computer scientist who helped create the software behind Quill and is a cofounder of the company. “Short-term and medium-term, [AI] will displace work but not necessarily jobs,” he says. If AI tools do some of the scut work involved in analyzing data, he says, people can be “free to work at the top of their game.”

And as impressive as Quill and other recent advances are, Hammond is not yet convinced that the capabilities of general-purpose AI are poised for great expansion. The current resurgence in the field, he says, is being driven by access to massive amounts of data that can be quickly analyzed and by the immense increase in computing power over what was available a few years ago. The results are striking, but the techniques, including some aspects of the natural-language generation methods that Quill employs, make use of existing technologies empowered by big data, not breakthroughs in AI. Hammond says some recent descriptions of certain AI programs as black boxes that teach themselves capabilities sound more like “magical rhetoric” than realistic explanations of the technology. And it remains uncertain, he adds, whether deep learning and other recent advances will truly “work as well as touted.”

In other words, it would be smart to temper our expectations about the future possibilities of machine intelligence.

The gods of technology

“Too often technology is discussed as if it has come from another planet and has just arrived on Earth,” says Anthony Atkinson, a fellow of Nuffield College at the University of Oxford and a professor at the London School of Economics. But the trajectory of technological progress is not inevitable, he says: rather, it depends on choices by governments, consumers, and businesses as they decide which technologies get researched and commercialized and how they are used.

Atkinson has been studying income inequality since the late 1960s, a period when it was generally a subject on the back burner of mainstream economics. Over those years, income inequality has grown dramatically in a number of countries. Its levels rose in the U.K. in the 1980s and have not fallen since, and in the United States they are still rising, reaching historically unprecedented heights. The publication last year of his frequent collaborator Thomas Piketty’s remarkably successful Capital in the 21st Century made inequality the hottest topic in economics. Now Atkinson’s new book, called Inequality: What Can Be Done?, proposes some solutions. First on his list: “encouraging innovation in a form that increases the employability of workers.”

When governments choose what research to fund and when businesses decide what technologies to use, they are inevitably influencing jobs and income distribution, says Atkinson. It’s not easy to see a practical mechanism for picking technologies that favor a future in which more people have better jobs. But “at least we need to ask” how these decisions will affect employment, he says. “It’s a first step. It might not change the decision, but we will be aware of what is happening and don’t have to wait until we say, ‘Oh dear, people have lost their jobs.’”

Part of the strategy could emerge from how we think about productivity and what we actually want from machines. Economists traditionally define productivity in terms of output given a certain amount of labor and capital. As machines and software—capital—become ever cheaper and more capable, it makes sense to use less and less human labor. That’s why the prominent Columbia University economist Jeffrey Sachs recently predicted that robots and automation would soon take over at Starbucks. But there are good reasons to believe that Sachs could be wrong. The success of Starbucks has never been about getting coffee more cheaply or efficiently. Consumers often prefer people and the services humans provide.

Take the hugely popular Apple stores, says Tim O’Reilly, the founder of O’Reilly Media. Staffed by countless swarming employees armed with iPads and iPhones, the stores provide a compelling alternative to a future of robo-retail; they suggest that automating services is not necessarily the endgame of today’s technology. “It’s really true that technology will take away a class of jobs,” says O’Reilly. “But there is a choice in how we use technology.”

In that sense, Apple stores have found a winning strategy by not following the conventional logic of using automation to lower labor costs. Instead, the company has cleverly deployed an army of tech-savvy sales employees toting digital gadgets to offer a novel shopping experience and to profitably expand its business.

O’Reilly also points to the enormous success of the car service Uber. By using technology to create a convenient and efficient reservation and payment service, it has created a robust market. And in doing so, it has expanded the demand for drivers—who, with the aid of a smartphone and app, now have greater opportunities than they might working for a conventional taxi service.

The lesson is that if advances in technology are playing a role in increasing inequality, the effects are not inevitable, and they can be altered by government, business, and consumer decisions. As the economist Paul Krugman recently told an audience at a forum called “Globalization, Technological Change, and Inequality” in New York City, “A lot of what’s happening [in income inequality] is not just the gods of technology telling us what must happen but is in fact [due to] social constructs that could be different.”

Who owns the robots?

The effects of automation and digital technology on today’s employment picture are sometimes downplayed by those who point to earlier technology transitions. But that ignores the suffering and upheaval during those periods. Wages in England were stagnant or fell for around 40 years after the beginning of the Industrial Revolution, and the misery of factory workers is well documented in the literature and political writings of the day.

In his new book, The Great Divide, the Columbia University economist Joseph Stiglitz suggests that the Great Depression, too, can be traced to technological change: he says its underlying cause was not, as is typically argued, disastrous government financial policies and a broken banking system but the shift from an agricultural economy to a manufacturing one. Stiglitz describes how the advent of mechanization and improved farming practices quickly transformed the United States from a country that needed many farmers to one that needed relatively few. It took the manufacturing boom fueled by World War II to finally help workers through the transition. Today, writes Stiglitz, we’re caught in another painful transition, from a manufacturing economy to a service-based one.

Those who are inventing the technologies can play an important role in easing the effects. “Our way of thinking as engineers has always been about automation,” says Hod Lipson, the AI researcher. “We wanted to get machines to do as much work as possible. We always wanted to increase productivity; to solve engineering problems in the factory and other job-related challenges is to make things more productive. It never occurred to us that isn’t a good thing.” Now, suggests Lipson, engineers need to rethink their objectives. “The solution is not to hold back on innovation, but we have a new problem to innovate around: how do you keep people engaged when AI can do most things better than most people? I don’t know what the solution is, but it’s a new kind of grand challenge for engineers.”

Ample opportunities to create jobs could come from much-needed investments in education, aging infrastructure, and research in areas such as biotechnology and energy. As Martin Ford rightly warns, we could be in for a “perfect storm” if climate change grows more severe at a time when technological unemployment imposes increased economic pressure. Whether this happens will depend in large part on which technologies we invent and choose to embrace. Some version of an automated vehicle seems inevitable, for example; do we use this to make our public transportation systems more safe, convenient, and energy efficient, or do we simply fill the highways with driverless cars and trucks?

There is little doubt that at least in the short term, the best bulwark against sluggish job creation is economic growth, whether that’s accomplished through innovative service-intensive businesses like the Apple stores and Uber or through investments in rebuilding our infrastructure and education systems. It is just possible that such growth will overcome the worries over robots taking our jobs.

Andrew McAfee, the coauthor with his MIT colleague Erik Brynjolfsson of The Second Machine Age, has been one of the most prominent figures describing the possibility of a “sci-fi economy” in which the proliferation of smart machines eliminates the need for many jobs. (See “Open Letter on the Digital Economy,” in which McAfee, Brynjolfsson, and others propose a new approach to adapting to technological changes.) Such a transformation would bring immense social and economic benefits, he says, but it could also mean a “labor-light” economy. “It would be a really big deal, and it’s not too soon to start the conversation about it,” says McAfee. But it’s also, he acknowledges, a prospect that is many decades away. Meanwhile, he advocates pro-growth policies “to prove me wrong.” He says, “The genius of capitalism is that people find things to do. Let’s give it the best chance to work.”

Here’s the rub. As McAfee and Brynjolfsson explain in TheSecond Machine Age, one of the troubling aspects of today’s technological advances is that in financial terms, a few people have benefited from them disproportionately (see “Technology and Inequality”). As Silicon Valley has taught us, technology can be both a dynamic engine of economic growth and a perverse intensifier of income inequality.

Whoever owns the capital will benefit as robots and artificial intelligence inevitably replace many jobs.

In 1968, J.C.R. Licklider, one of the creators of today’s technology age, co-wrote a remarkably prescient article called “The Computer as a Communication Device.” He predicted “on line interactive communities” and explained their exciting possibilities. Licklider also issued a warning at the end of the paper:

“For the society, the impact will be good or bad, depending mainly on the question: Will ‘to be on line’ be a privilege or right? If only a favored segment of the population gets a chance to enjoy the advantage of ‘intelligence amplification,’ the network may exaggerate the discontinuity in the spectrum of intellectual opportunity.”

Various policies can help redistribute wealth or, like the guaranteed basic income, provide a safety net for those at or near the bottom. But surely the best response to the economic threats posed by digital technologies is to give more people access to what Licklider called “intelligence amplification” so that they can benefit from the wealth new technology creates. That will mean providing fairer access to quality education and training programs for people throughout their careers.

It also means, says Richard Freeman, a leading labor economist at Harvard University, that far more people need to “own the robots.” He’s talking not only about machines in factories but about automation and digital technologies in general. Some mechanisms already exist in profit-sharing programs and employee stock-ownership plans. Other practical investment programs can be envisioned, he says.

Whoever owns the capital will benefit as robots and AI inevitably replace many jobs. If the rewards of new technologies go largely to the very richest, as has been the trend in recent decades, then dystopian visions could become reality. But the machines are tools, and if their ownership is more widely shared, the majority of people could use them to boost their productivity and increase both their earnings and their leisure. If that happens, an increasingly wealthy society could restore the middle-class dream that has long driven technological ambition and economic growth.